Flow Identification for Supporting Resource Reservation

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Abstract

This paper considers the problem of flow identification for supporting
resource reservation. We propose several hashing-based schemes for flow
identification and present a quantitative analysis of their performance and
scalability limits. Of the hash functions we studied using simulation with
real traffic traces, 32-bit CRC and XOR-folding of the five-tuple
demonstrate excellent performance, both on the memory requirement for a
collision rate target, and on the number of collided flows on average and in
the worst-case. Our findings show that, with hashing-based schemes, it is
feasible to implement flow identification at high speeds to support hundreds
of thousands of reserved flows.